CNN-Based Intelligent 3D Path Planning Algorithm in the Framework of the Improved Lazy Theta*

Yuwan Yin, Xin Ning

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In this paper, a CNN-based intelligent path planning algorithm in the framework of the improved Lazy theta* is proposed to solve the problem of path planning in the 3D terrain environment. The key point of the proposed algorithm is that the safety factor and the total length of the path will be comprehensively considered. By considering these two factors, a short, safe and smooth path can be planned efficiently and automatically in a 3D terrain environment. In order to solve the problem of the path moving close to the edge of the obstacles and passing dangerously between multiple obstacles, CNN is used to create a continuous and safe 3D topographic map and improve the ways of node expansion to ensure the safety of the path. Moreover, a weight self-adjustment strategy is introduced to optimize the path cost function, which solves the problem of the low search efficiency. The simulation results show that compared with the ordinary A* algorithm and Lazy theta* algorithm, the path planned by the improved intelligent Lazy theta* algorithm proposed in this paper is safer and smoother, and the search efficiency is higher, which can be applied to different planning objects according to different task scenarios.

源语言英语
主期刊名Proceedings of 2021 International Conference on Autonomous Unmanned Systems, ICAUS 2021
编辑Meiping Wu, Yifeng Niu, Mancang Gu, Jin Cheng
出版商Springer Science and Business Media Deutschland GmbH
457-466
页数10
ISBN(印刷版)9789811694912
DOI
出版状态已出版 - 2022
活动International Conference on Autonomous Unmanned Systems, ICAUS 2021 - Changsha, 中国
期限: 24 9月 202126 9月 2021

出版系列

姓名Lecture Notes in Electrical Engineering
861 LNEE
ISSN(印刷版)1876-1100
ISSN(电子版)1876-1119

会议

会议International Conference on Autonomous Unmanned Systems, ICAUS 2021
国家/地区中国
Changsha
时期24/09/2126/09/21

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